Recent advancements in display technology are beginning to allow for an extended range of color, luminance and contrast to be displayed. Technologies allowing for extensions in luminance or brightness range of image content are known as high dynamic range imaging, often shortened to HDR. HDR technologies focus on capturing, processing and displaying content of a wider dynamic range.
Although a number of HDR display devices have appeared, and image cameras capable of capturing images with an increased dynamic range are being developed, there is still very limited HDR content available. While recent developments promise native capture of HDR content in the near future, they do not address existing content.
To prepare conventional (hereon referred to as LDR for low dynamic range) content for HDR display devices, reverse or inverse tone mapping operators (ITMO) can be employed. Such algorithms process the luminance information of colors in the image content with the aim of recovering or recreating the appearance of the original scene. Typically, ITMOs take a conventional (i.e. LDR) image as input, expand the luminance range of the colors of this image in a global manner, and subsequently process highlights or bright regions locally to enhance the HDR appearance of colors in the image.
Although several ITMO solutions exist, they focus at perceptually reproducing the appearance of the original scene and rely on strict assumptions about the content. Additionally, most expansion methods proposed in the literature are optimized towards extreme increases in dynamic range.
Typically, HDR imaging is defined by an extension in dynamic range between dark and bright values of luminance of colors combined with an increase in the number of quantization steps. To achieve more extreme increases in dynamic range, many methods combine a global expansion with local processing steps that enhance the appearance of highlights and other bright regions of images. Known global expansion steps proposed in the literature vary from inverse sigmoid, to linear or piecewise linear.
To enhance bright local features in an image, it is known to create a luminance expansion map, wherein each pixel of the image is associated with an expansion value to apply to the luminance of this pixel using some function.
The luminance expansion step increases the contrast in the image so that it is better suited for HDR displays. However often, at the same time, this step increases the contrast of artifacts or noise in the image, making such artifacts more visible and therefore more disturbing to the viewers. For that purpose, it might be desirable to denoise the image. If an existing denoising process is applied before or after the ITMO as a separate process, many additional computations will be required.
This disclosure is closely related to published application WO2015096955, filed 2 Dec. 2014, entitled “METHOD FOR INVERSE TONE MAPPING AN IMAGE” which is incorporated by reference. In comparison with this document, this invention mainly adapts the expansion process in order to reduce noise in the image in a computationally efficient manner, minimizing additional processing.